A secure inference over Deep Neural Networks (DNNs) using secure two-party computation to perform privacy-preserving machine learning. The secure inference uses a particular type of comparison that can be used as a building block for various layers in the DNN including, for example, ReLU activations and divisions. The comparison securely computes a Boolean share of a bit representing whether input value x is less than input value y, where x is held by a user of the DNN, and where y is held by a provider of the DNN. Each party computing system parses their input into leaf strings of multiple bits. This is much more efficient than if the leaf strings were individual bits. Accordingly, the secure inference described herein is more readily adapted for using in complex DNNs.

A vehicle control method of starting and shutting down an engine, in which a processor receives a blockchain update comprising a first transaction with instructions to perform an engine startup or shutdown; the blockchain update is validated; an engine startup or shutdown is performed based on the validated blockchain update; where the engine startup or shutdown is delayed based on validating a predetermined number of subsequent blockchain updates, including a second transaction with instructions to perform the engine startup or shutdown.

A vehicle control method of starting and shutting down an engine, in which a processor receives a blockchain update comprising a first transaction with instructions to perform an engine startup or shutdown; the blockchain update is validated; an engine startup or shutdown is performed based on the validated blockchain update; where the engine startup or shutdown is delayed based on validating a predetermined number of subsequent blockchain updates, including a second transaction with instructions to perform the engine startup or shutdown.

An example operation may include one or more of generating an initial seed and allocating one or more authorized bits of the initial seed to a plurality of blocks in a distributed ledger, storing the initial seed and an identification of which authorized bits of the initial seed are allocated to each block of the distributed ledger, receiving a final seed value that is partially generated by each of a plurality of nodes configured to access the distributed ledger based on authorized bits of respective blocks updated by each respective node, and generating a random sequence value based on the final seed value and storing the random sequence value in a block of the distributed ledger.

An example operation may include one or more of generating an initial seed and allocating one or more authorized bits of the initial seed to a plurality of blocks in a distributed ledger, storing the initial seed and an identification of which authorized bits of the initial seed are allocated to each block of the distributed ledger, receiving a final seed value that is partially generated by each of a plurality of nodes configured to access the distributed ledger based on authorized bits of respective blocks updated by each respective node, and generating a random sequence value based on the final seed value and storing the random sequence value in a block of the distributed ledger.

N key generation circuits are arranged in a pipeline having N stages. Each key generation circuit is configured to generate a round key as a function of a respective input key and a respective round constant. Output signal lines that carry the round key from a key generation circuit in a stage of the pipeline, except the key generation circuit in a last stage of the pipeline, are coupled to the key generation circuit in a successive stage of the pipeline to provide the respective input key.

N key generation circuits are arranged in a pipeline having N stages. Each key generation circuit is configured to generate a round key as a function of a respective input key and a respective round constant. Output signal lines that carry the round key from a key generation circuit in a stage of the pipeline, except the key generation circuit in a last stage of the pipeline, are coupled to the key generation circuit in a successive stage of the pipeline to provide the respective input key.

Software installed in the nodes in a communication network allows them to perform a “name server” function, which entails the management of a dynamic list of the client devices that are connected to the cloud, a “task” function, which entails the receipt and transmission of the packets, and an “authority” function, which entails the determination of the routes of the packets through the cloud. Each node is capable of performing only one function at a time. After completing a job, a node reverts to an undifferentiated, state awaiting its next performance request.

Software installed in the nodes in a communication network allows them to perform a “name server” function, which entails the management of a dynamic list of the client devices that are connected to the cloud, a “task” function, which entails the receipt and transmission of the packets, and an “authority” function, which entails the determination of the routes of the packets through the cloud. Each node is capable of performing only one function at a time. After completing a job, a node reverts to an undifferentiated, state awaiting its next performance request.

A device for communication includes a processor and a transmitter. The processor is configured to determine a target quality of service (QoS). The processor is also configured to determine, based on the target QoS, a transmission schedule identifying one or more transmission time-blocks. The transmitter is configured to transmit data to at least one device during a transmission time-block of the one or more transmission time-blocks.